CN105554739B - Primary user based on channel multi-path delay inequality emulates attack detection method - Google Patents
Primary user based on channel multi-path delay inequality emulates attack detection method Download PDFInfo
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- CN105554739B CN105554739B CN201510900340.4A CN201510900340A CN105554739B CN 105554739 B CN105554739 B CN 105554739B CN 201510900340 A CN201510900340 A CN 201510900340A CN 105554739 B CN105554739 B CN 105554739B
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Abstract
The present invention relates to a kind of, and the primary user based on channel multi-path delay inequality emulates attack detection method.In existing method when PUE user can obtain the prior information of PU and with ability is reconfigured, detection efficiency can be greatly reduced.The present invention carries out channel estimation by the method and obtains the multipath fading feature of channel, and realizes that primary user emulates the detection of attack using the method for dualism hypothesis detection according to this feature.Specifically according to the multipath fading model of fixed scene lower channel, cognitive radio users carry out the multidiameter delay that channel is calculated in computing cross-correlation using the preamble information docking collection of letters number of primary user and synchronizing sequence, and the delay inequality of two diameters of multipath amplitude maximum is then selected to make judgement as binary hypothesis test object.The method of the present invention need only obtain the preamble information of primary user, be not necessarily to channel background noise power, and can work normally when emulating the large scale and mesoscale fading characteristic of primary user's success simulated main customer.
Description
Technical field
Patent of the present invention belongs to cognitive radio security fields, is related to a kind of feelings in energy measuring and variance detection failure
Under condition, the method that primary user emulates attack is detected by channel multipath fading feature.
Background technology
Cognitive radio networks (Cognitive Radio Network, CRN) can effectively improve frequency spectrum resource utilization
Rate alleviates the frequency spectrum resource anxiety problem of current getting worse.Its operation principle is not interfere authorized user in the frequency range
I.e. under conditions of primary user (Primary User, PU) normal work, perception user (Secondary User, SU) passes through frequency spectrum
Cognition technology obtains " frequency spectrum cavity-pocket " i.e. idle frequency spectrum information and waits for an opportunity to access these frequency spectrum cavity-pockets, to shared frequently with primary user
Spectrum resource.But this working mechanism, which is also CRN, introduces a series of new safety problems.
It is one of which Denial of that primary user, which emulates attack (Primary User Emulation Attack, PUEA),
Service (Dos) is attacked, and is a kind of huge potential collision hazard in CRN.Primary user emulates user (PUE) and passes through simulated main customer
Signal characteristic, so that the SU of normal work is mistakenly considered current frequency range and be currently being used, to reach exclusive idle frequency spectrum resource or
It does not allow other SU to access the purpose of idle frequency spectrum, seriously destroys the normal work of CRN.
The method of existing detection PUEA mainly has transmitter geographical location to detect (Location detection) at present,
Energy measuring (Energy Detection), is closed at channel characteristics detection (Channel Characteristics Detection)
Detect (Cooperative Detection) and fingerprint detection (Fingerprint Detection).It is geographical in PU transmitters
In the case that position is priori, the detection method based on geographical location can be examined by distance ratio detection method, distance difference
The methods of survey method, received signal strength detection method detect the geographical location of emission source, to determine whether there are frequency spectrum cavity-pocket, this
Kind of method PU and SU distance farther out when there is preferable effect.Method based on energy measuring have computation complexity it is low,
The advantages of being easily achieved, such as the energy measuring method based on Fenton approximation methods and Markov inequality, but this method is held
It is vulnerable to the attack of PUEA, can be substantially reduced when primary user emulates when user (PUE) is adjusted transmission power in attack
Defending performance.Channel characteristics detection is identified according to PU transmitters and PUE transmitters to the different principle of the channel characteristics between SU
Receive signal, such as calculate and receive the variance of signal and can obtain the channel characteristics of Lognormal shadowing, this method it is excellent
Point is to insensitive for noise, the disadvantage is that implementation complexity is high and detection time is longer.Cooperative detection is the detection based on single SU
Basis is promoted overall performance by way of cooperation and reduces the unstability of single user's detection, but is easy to bring negative
Effect such as perception data error attack.Fingerprint detection is then difficult to the feature being imitated such as carrier wave by finding in primary user's signal
Frequency, the features such as phase offset as detection object and are trained and are classified by the method for machine learning, but in primary user
It is easy to be imitated by PUE in the case of signal characteristic is known.
Mainly by detection transmitter feature and channel characteristics, (large scale and mesoscale of channel decline above-mentioned detection method
Fall feature) realize.In the CRN models based on TV networks, digital television ground broadcast transmission system (digital
Television terrestrial multimedia broadcasting, DTMB) signal structure, modulation system and geography
Position all can serve as the prior information of detection, but the primary user for having sensing capability emulates more than user also can accurately imitate
Feature, in this case, it would be desirable to find a kind of new detection method to identify PUEA.
Invention content
In view of the deficiencies of the prior art, the present invention provides the primary users based on channel multi-path delay inequality to emulate attack detecting side
Method.By this method to the CRN based on TV networks under fixed scene, (believed by transmitter feature or channel characteristics when existing
The large scale and mesoscale fading characteristic in road) realize the method failures of PUEA detections in the case of, establish a kind of system model, it is real
PUEA detection methods now based on channel multipath fading feature.
The method of the invention receives the undergone multipath of signal known to DTMB preamble informations, by estimation
Intrinsic parameter, that is, multidiameter delay difference of channel identifies that primary user's signal and primary user emulate signal.The present invention has computing overhead
It is low, short and not high to the noise sensitivity feature of recognition time, and institute's identification parameter can not be imitated by PUE, detection probability is high,
There is good application prospect in CRN based on TV networks.
To achieve the goals above, the technical solution adopted in the present invention the specific steps are：
Step 1：With digital television ground broadcast transmission system in the cognitive radio networks of primary user, SU is in PU works
When making, estimate to obtain the delay inequality between multipath amplitude maximum diameter and the second diameter by channel multi-path time delay estimation method, and
As judgement prior information, then according to false-alarm probability PFPIt is required that setting decision threshold value δ, detailed process are as follows：It is described
SU be perception user, PU is user；
(1) SU is with frequency fsWorking signal in current spectral is sampled, obtain receive signal be y (n), y (n)=
s(n)*h(n)+w(n)；
Wherein s (n) indicates that transmitting signal sequence, the transmitting each data frame of signal are L by lengthPNPreamble sequence PN (n)
It is L with lengthdFrame sequence d (n) two parts composition, PN (n) include length be LpreGroup of preamble symbols sequence, length Lm
9 rank m-sequence of cyclic extensions and length be LpostRear synchronizing symbol sequence；H (n) indicates multipath channel response；W (n) is indicated
Interchannel noise；* linear convolution is indicated.
(2) SU locally generates sequence C (n) identical with transmitting signal m-sequence according to the preamble information of PU in receiving terminal；
The autocorrelation performance of C (n) is as follows：
Wherein RCC(n) autocorrelation value of C (n) is indicated,Indicate C (n) with LmIt is obtained for period expansion
Cyclic sequence.
C (n) and y (n) is subjected to linear cross-correlation evaluation, obtains the cross correlation value R of C (n) and y (n)yC(n), it calculates such as
Under：
WhereinIndicate that related operation, w ' (n) indicate the cross correlation value of w (n) and C (n).
The linear cross correlation value R of s (n) and C (n) are obtained by the data frame structure of transmitting signalsC(n)：
RsC(n) consist of two parts, first part is the cross correlation value R of preamble sequence PN (n) and m-sequencepC(n),
Two parts are the cross correlation value R of data frame signal d (n) and m-sequencedC(n)。
According to the autocorrelation performance of C (n), RpC(n) result of calculation is as follows：
Then RpC(n+Lpre)=G δ (n)+I (n), n=-Lpre,...,Lpost；
Wherein, G is middle coefficient, G=RpC(Lpre)；δ (n) is impulse function；I (n) is RpC(n) in the form of impulse function
Appended sequence when expression,
When receiving terminal sample rate is sufficiently large, RyC(n) it is expressed as：
Wherein L indicates multipath number, hkAnd τkThe complex gain and additional time delay of k-th of multipath component are indicated respectively.
(3) synchronizing symbol sequence time duration T after channel maximum multipath time delay difference is less thanpostWhen, calculate multipath letter
The amplitude of every, road diameter Wherein Tpost=LpostTs, TsIndicate the unit symbol of signal frame
Time span；Thus R is foundyC(n) in [Lpre,Lpre+Lpost] in cross-correlation peak value, time point where each peak value corresponds to
The opposite multidiameter delay of the diameter.
(4) algorithm process is ranked up to the peak point obtained in (3), finds the time point of two diameters of amplitude maximum,
The two time points are the opposite multidiameter delay of corresponding two diameter of multipath amplitude maximum, calculate the delay inequality △ τ of the twoPU。
(5) the above estimation procedure, counting statistics average value are repeatedWhereinIndicate ith
Multidiameter delay difference estimated value, N are estimation number.
(6) according to preset false-alarm probability PFPIt is required that by
Setting meets PFPMinimum decision threshold value δ, Pr indicate probability value.
When unknown subscriber works, acquisition receives signal y (n) by step 2, SU；Pass through the channel multi-path delay inequality in step 1
The delay inequality between multipath amplitude maximum diameter and the second diameter is calculated in method of estimation, repeats to estimate n times, obtains assembly average
Step 3, SU judge that the signal received comes from PU or PUE, PUE is primary by building binary hypothesis test
Family emulates user；It is as follows that SU builds binary hypothesis test：
The multidiameter delay that the decision threshold value δ and step 2 obtained according to step 1 is obtained is poorSU is done by following criterion
Go out judgement：
The present invention is that the primary user based on channel multi-path delay inequality emulates attack detection method, with past detection method phase
Than advantage is embodied in：
1, existing PUEA detection methods are all based on transmitter feature, channel large-scale characteristics and mesoscale characteristics come into
Row identification, when PUE user can obtain the prior information of PU and with reconfigure ability when, detection efficiency can significantly under
Drop.The present invention is based on a kind of multipath fading feature, that is, channel multi-path delay inequalitys of channel to be identified, can PUE user at
It is worked normally when the large-scale decline and mesoscale fading characteristic of work(simulated main customer.
2, for the present invention for the CRN based on TV networks under fixed scene, identification only needs the preamble information of TV transmitting signals,
Short with recognition time, hardware configuration requires low and the characteristics of to insensitive for noise, is suitble to limited in computing capability, needs quickly
It is used in the CRN of identification.
3, for the present invention using multidiameter delay difference as the characteristic parameter of detection, this feature parameter belongs to the intrinsic parameter of channel,
And with the geographical location of transmitter and receiver change and change, therefore PUE user can not by study with reconfiguration course into
Row imitates, and detection probability is high.
Description of the drawings
Fig. 1 is the CRN models based on TV networks proposed.
Fig. 2 is that the primary user based on channel multi-path delay inequality emulates attack detection method.
Fig. 3 is the channel multi-path delay inequality computational methods flow chart based on DTMB preamble informations.
Specific implementation mode
The present invention is described in further details below in conjunction with the attached drawing embodiment that develops simultaneously.
This example is operated in the CRN based on TV under fixed scene, as shown in Figure 1, the environment meets the following conditions：
(1) PU transmitter sites are fixed, and SU and malicious node static state are deployed in distance PU transmitters dpA radius be R
Border circular areas in, and have R ＜ ＜ dp。
(2) malicious node has the ability for reconfiguring transmission power.
(3) SU is received considers path loss (path loss), Lognormal shadowing from the signal of PU and malicious node
The influence of Rayleigh fading (Rayleigh fading) caused by (log-normal shadowing) and multipath effect is lost.
(4) malicious user can imitate the large-scale decline and mesoscale fading characteristic of PU.
Such as Fig. 2, this example is realized especially by following steps：
Step 1, SU estimate to obtain multipath when PU works by channel multi-path time delay estimation method as shown in Figure 3
Delay inequality between amplitude maximum diameter and the second diameter, and as judgement prior information, then according to false-alarm probability PFPIt is required that
Decision threshold value δ is set, detailed process is as follows：
(1) setting sample frequency fs=Ns/Ts, wherein TsIndicate the unit symbol time span of signal frame, NsValue is 8；
Receiving terminal signal-to-noise ratio is set in 0dB or more.SU samples to obtain reception signal
Y (n)=s (n) * h (n)+w (n)；
Y (n) is handled as follows according to sample frequency,
(2) SU is by m-sequence C (n) in linear shift register generation PU preamble sequences synchronous with initial vector, to y
(n) linear cross-correlation evaluation is carried out with C (n), it is as a result as follows：
WhereinN=Lpre,Lpre+1...,Lpre+Lpost, wherein LmIndicate sequence
The length of C (n) is arranged, it is 511 to be worth；LpostIndicate the rear synchronizing symbol sequence length of preamble sequence, it is 217 to be worth；LpreBefore expression
The group of preamble symbols sequence length of code-guiding sequence, it is 217 to be worth.
(3) to RyC(n) value does sequence processing, and wherein n value ranges are [Lpre,Lpre+Lpost]；Find RyC(n) value is most
Two big n values, n1And n2；Then the delay inequality between the channel multi-path amplitude maximum diameter and the second diameter of primary user is △ τPU=|
n1-n2|Ts。
(4) the above estimation procedure, counting statistics average value are repeatedWhereinIt is ith
Multidiameter delay difference estimated value, N be estimation number.
(5) setting false-alarm probability PFP=0.2, by
It finds out and meets PFPMinimum decision threshold value δ.
Step 2, SU set sample frequency as f when unknown subscriber workss, obtain receiving signal y (n)；Pass through Fig. 3 institutes
The delay inequality between multipath amplitude maximum diameter and the second diameter is calculated in the channel multi-path time delay estimation method shown
Step 3, SU judge that the signal received comes primary user or primary user's emulation by building binary hypothesis test
User.It is as follows that SU builds binary hypothesis test：
The multidiameter delay that the decision threshold value δ and step 2 obtained according to step 1 is obtained is poorSU is done by following criterion
Go out judgement：
Claims (2)
1. the primary user based on channel multi-path delay inequality emulates attack detection method, it is characterised in that this method includes following step
Suddenly：
Step 1：With digital television ground broadcast transmission system, in the cognitive radio networks of primary user, SU works in PU
When, estimate to obtain the delay inequality between multipath amplitude maximum diameter and the second diameter by channel multi-path time delay estimation method, and will
It is as judgement prior information, then according to false-alarm probability PFPIt is required that setting decision threshold value δ：The SU is perception user,
PU is primary user；
Step 2：For SU when unknown subscriber works, acquisition receives signal y (n)；Pass through the channel multi-path time delay estimation in step 1
The delay inequality between multipath amplitude maximum diameter and the second diameter is calculated in method, repeats to estimate n times, obtains assembly average
Step 3：SU judges that the signal received comes from PU or PUE, PUE is imitative for primary user by building binary hypothesis test
True user；It is as follows that SU builds binary hypothesis test：
The multidiameter delay that the decision threshold value δ and step 2 obtained according to step 1 is obtained is poorSU is made by following criterion to be sentenced
Certainly：
2. the primary user based on channel multi-path delay inequality emulates attack detection method as described in claim 1, it is characterised in that
Described in step 1 according to false-alarm probability PFPIt is required that setting decision threshold value δ's comprises the concrete steps that：
(1) SU is with frequency fsWorking signal in current spectral is sampled, obtains receiving signal being y (n), y (n)=s (n) *
h(n)+w(n)；
Wherein s (n) indicates that transmitting signal sequence, the transmitting each data frame of signal are L by lengthPNPreamble sequence PN (n) and long
Degree is LdFrame sequence d (n) two parts composition, PN (n) include length be LpreGroup of preamble symbols sequence, length LmFollow
Ring extends 9 rank m-sequences and length is LpostRear synchronizing symbol sequence；H (n) indicates multipath channel response；W (n) indicates channel
Noise；* linear convolution is indicated；
(2) SU locally generates sequence C (n) identical with transmitting signal m-sequence according to the preamble information of PU in receiving terminal；C(n)
Autocorrelation performance it is as follows：
Wherein RCC(n) autocorrelation value of C (n) is indicated,Indicate C (n) with LmThe cycle sequence obtained for period expansion
Row；
C (n) and y (n) is subjected to linear cross-correlation evaluation, obtains the cross correlation value R of C (n) and y (n)yC(n), it calculates as follows：
WhereinIndicate that related operation, w ' (n) indicate the cross correlation value of w (n) and C (n)；
The linear cross correlation value R of s (n) and C (n) are obtained by the data frame structure of transmitting signalsC(n)：
RsC(n) consist of two parts, first part is the cross correlation value R of preamble sequence PN (n) and m-sequencepC(n), second
Point it is the cross correlation value R of data frame signal d (n) and m-sequencedC(n)；
According to the autocorrelation performance of C (n), RpC(n) result of calculation is as follows：
Then RpC(n+Lpre)=G δ (n)+I (n), n=-Lpre,...,Lpost；
Wherein, G is middle coefficient, G=RpC(Lpre)；δ (n) is impulse function；I (n) is RpC(n) it is indicated in the form of impulse function
When appended sequence,
When receiving terminal sample rate is sufficiently large, RyC(n) it is expressed as：
Wherein L indicates multipath number, hkAnd τkThe complex gain and additional time delay of k-th of multipath component are indicated respectively；
(3) synchronizing symbol sequence time duration T after channel maximum multipath time delay difference is less thanpostWhen, calculate multipath channel every
The amplitude of diameterWherein Tpost=LpostTs, TsIndicate that the unit symbol time of signal frame is long
Degree；Thus R is foundyC(n) in [Lpre,Lpre+Lpost] in cross-correlation peak value, the time point where each peak value corresponds to the diameter
Opposite multidiameter delay；
(4) algorithm process is ranked up to the peak point obtained in (3), finds the time point of two diameters of amplitude maximum, this two
A time point is the opposite multidiameter delay of corresponding two diameter of multipath amplitude maximum, calculates the delay inequality Δ τ of the twoPU；
(5) the above estimation procedure, counting statistics average value are repeatedWhereinIndicate the multipath of ith
Time delay estimation value, N are estimation number；
(6) according to preset false-alarm probability PFPIt is required that by
Setting meets PFPMinimum decision threshold value δ, Pr indicate probability value.
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| CN106162620B (en) * | 2016-08-12 | 2019-05-03 | 浙江大学 | A kind of primary user's emulation attack detection method based on channel Doppler effect |
| CN106452674B (en) * | 2016-09-30 | 2019-04-12 | 西安交通大学 | A kind of actual data packet restoration methods based on 802.11ac network |
| CN107086921B (en) * | 2017-04-18 | 2020-04-24 | 桂林电子科技大学 | User identity identification method based on small cell spectrum auction system |
| CN107332855B (en) * | 2017-07-20 | 2020-04-28 | 浙江大学 | Main user simulation attack detection method based on reinforcement learning algorithm |
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